Reverse-engineering causal graphs with soft interventions
I am currently a Research Staff Member at IBM Research AI, NY. Previously, I was a Herman Goldstine Postdoctoral Fellow in the Math Sciences Division at IBM Research, NY. I obtained my Ph.D. in Electrical and Computer Engineering from UT Austin in summer 2016. My advisor at UT was Alex Dimakis. I obtained my MS degree in Electrical Engineering (2010-2012) from the University of Southern California, B.Tech and M.Tech degrees in Electrical Engineering from IIT Madras in 2010.
My research interests broadly lie in Graph algorithms, Machine learning, Optimization, Coding Theory and Information Theory. In machine learning, my recent focus is on graphical model learning, causal inference interpretability in ML and large graph analytics. I also work on problems relating to information flow, storage and caching over networks.
Publications with the MIT-IBM Watson AI Lab